class_docstr: Base class of samplers.
  
  Args:
      num (int): Number of samples
      pos_fraction (float): Fraction of positive samples
      neg_pos_up (int): Upper bound number of negative and
          positive samples. Defaults to -1.
      add_gt_as_proposals (bool): Whether to add ground truth
          boxes as proposals. Defaults to True.
docstr: Sample positive samples.
docstr_tok: ["Sample","positive","samples","."]
code: def _sample_pos(
      self, assign_result: AssignResult, num_expected: int, **kwargs
  ):
      """Sample positive samples."""
      pass
  
file_path: mmdetection/mmdet/models/task_modules/samplers/base_sampler.py
imports: from abc import ABCMeta, abstractmethod
  import torch
  from mmengine.structures import InstanceData
  from mmdet.structures.bbox import BaseBoxes, cat_boxes
  from ..assigners import AssignResult
  from .sampling_result import SamplingResult
label_desc: Use image node_id 2 for calling the BaseSampler obj's underlying member method code with example usage: obj._sample_pos(assign_result, num_expected) without return types